Nazleeni Samiha Haron

A system architecture for water quality monitoring system using wired sensors

This research paper proposes an aarchitecture for implementing a water quality monitoring system for the aquaculture industry. The system would enable monitoring of the water quality remotely via GSM. Conventional method used by aqua farms requires technical staff to visit ponds at designated time and perform manual testing on the water quality. Consequently, the technique consumes a lot of time and effort. This research project would focus on developing a prototype that can evaluate data collected through three criteria: Dissolved oxygen level, pH level, and temperature level. The system would also be able to send alert messages upon detecting degradation of water quality in the pond via SMS.

Agent Based Priority Heuristic for Job Scheduling on Computational Grids

Abstract A grid is an infrastructure for resource sharing. At present, many scientific applications require high computing power in processing, which can only be achieved by using the computational grid. For the selection and allocation of grid resources to current and future applications, grid job scheduling is playing a very vital role for computational grids. They constitute the building blocks for making grids available to the society. The efficient and effective scheduling policies, when assigning different jobs to specific resources, are very important for a grid to process high computing intensive applications. This paper presents an agent based job scheduling algorithm for efficient and effective execution of user jobs. This paper also includes the comparative performance analysis of our proposed job scheduling algorithm along with other well known job scheduling algorithms considering the quality of service parameters like waiting time, turnaround time, response time, total completion time, bounded slowdown time and stretch time. We also conducted the QoS based evaluation of the scheduling algorithms on an experimental computational grid using real workload traces. Experimental evaluation confirmed that the proposed grid scheduling algorithms posses a high degree of optimality in performance, efficiency and scalability. This paper also includes a statistical analysis of real workload traces to present the nature and behavior of jobs.

Parallelization of Edge Detection Algorithm using MPI on Beowulf Cluster

In this paper, we present the design of parallel Sobel edge detection algorithm using Foster’s methodology. The parallel algorithm is implemented using MPI message passing library and master/slave algorithm. Every processor performs the same sequential algorithm but on different part of the image. Experimental results conducted on Beowulf cluster are presented to demonstrate the performance of the parallel algorithm.

Remote monitoring using sensor in greenhouse agriculture

This paper proposes a monitoring system that can remotely monitor and predict changes of humidity and temperature level in the greenhouse atmosphere. The objective of the research project is to implement an agro-environmental remote monitoring system using wired sensor and issue SMS notification. The system will includes active measurements, which capable of detecting degradation level for humidity and temperature; and be equipped with an alert mechanism to notify workers about the atmosphere quality in the greenhouse so that precaution steps can be taken promptly. Hypothetical -Deductive method will be used as development methodology because it serves as the typical method in similar research field. With development of this Remote Monitoring System, it is hope that it will benefit farmers in term of bringing new technical innovation in collecting data and monitoring greenhouse.

Development of mobile learing tool

The widespread use of smart phones and mobile communication offers the opportunity to develop technology that will assist students to learn anytime and anywhere. This paper presents the development of M-learning tool for Windows mobile platform, in order to add values on the existing conventional and electronic learning. The system utilizes ASP.NET mobile web forms, Structured Query Language (SQL), and Extensible Markup Language (XML). This tool contains five modules that are lecture materials, assignment, academic information, discussion and quizzes. This paper also described the limitations of mobile phones in M-learning application development. The main objective of the research that has been carried out is to develop M-learning tool application using the Microsoft.Net infrastructure that runs on three-tier network architecture.

A proposed design for noise reduction algorithm in seismograph on High Performance Computing using F-K filter

This paper proposes a design of noise reduction algorithm for seismic data on a High Performance Computing (HPC) environment. The algorithm of interest is the F-k filter which can be optimized by executing it using parallel processing architecture. The implementation of the above mentioned noise filtering technique comprises of 3 stages which are Fast Fourier Transform followed by F-k filtering and finally inverse of Fast Fourier Transformation. Each of the slave nodes in the cluster would have the complete filtering algorithms and would be fed with the Seismic Shot Records in the form of binary codes. The number of Shot Records that would be given to a node at a given instance varies according to the complexity of each Shot Record. Load balancing is one of the major concerns for this project and that would be accomplished by the master node which acts as the coordinator for the entire process.

Green scheduling algorithm for a computational grid environment

Recently, the increasing demand for computing has led to the development of computational grids. Subsequently, the increased demand has also resulted in the significant heat management problem in the computational grid environment. The increased in computational workloads caused the servers to produce more heat, which consequently upsurges the cooling load. The extant research stated that the power supply for cooling such systems consumes quite a substantial portion (approximately 40% to 50%) of the total power consumption in a Data Center (DC). Current approaches addressing this problem include new cooling technology or optimizing cooling delivery. Alternatively, this paper proposes a green scheduling algorithm with the objective to minimize the cooling load by avoiding high thermal stress circumstances such as large hot spots and thermal violations while still maintaining the competitive performance in DC. The experimental results significantly showed that the proposed green scheduling algorithm was able to save the consumption of cooling load by 22.02% in DCs server room.

CO 2 corrosion rate determination mechanism implementing de Waard-Milliams model for oil & gas pipeline

Billions of ringgits are consistently being invested by the oil and gas companies to ensure pipeline integrity, especially to address problems caused by pipelines. However, the existing solutions in predicting corrosion occurrence often lead to an extremely high cost to be implemented. Worse, the current implementations require manual data entry, which lengthen the time taken for processing in order to obtain a reliable corrosion prediction. If a corroded pipeline failed to be predicted much earlier, the pipes might burst and will cause a significant chain of events that will affect the aqua eco-system. The companies will suffer huge financial losses to mitigate the catastrophic situation. Hence, a better pipeline corrosion determination mechanism needs to be developed to address the issues found in this dissertation. Through early prediction on the corrosion occurence, it will provide the user with the knowledge for a better decision making. This paper will deliberate on a system that predicts corrosion rate using the deWaard- Milliams model. Arduino UNO R3 was used in this project, in predicting the corrosion rate. As a proof of concept and performance, simulations were carried out using synthetic dataset to test the efficiency of the proposed system. Synthetic data was generated through the Gaussian function in Java. The proposed prototype was tested. Three types of testing were conducted which are data quality test, accuracy test and corrosion rate analysis. Data quality test is to ensure the synthetic data generated are closely matched with real data. Accuracy test evaluates the predicted corrosion rate against the real field data obtained from literature studies. Corrosion rate analysis provides an overview and comparison between the effects of the parameters determining the corrosion rate and the predicted corrosion rate. The results exhibit the capability of the mechanism to accurately predict the corrosion rate.

Conceptual design of pre-flood warning system based on user mobility

The occurrence of flood causes millions of damages, along with the loss of life and property and the devastation of agricultural and livestock. Therefore, an effective pre-flood warning system must be developed to mitigate flood losses and lessen the flood effects. However, when developing a warning system for flood disaster, limited communication during the occurrence and the availability of electricity should be taken into account. Thus, this paper proposes a conceptual framework with three (3) stages that consist of monitoring water level with reference to previous flood cases to determine flood danger status, alerting communities, passersby and local authorities regarding the water level and flood danger status and lastly is to notify flood victims to immediately go to the nearest relief center. By having an effective real time pre-flood warning system, immediate action can be carried out in order to save lives and minimize the damage caused by flood disaster.

Open source seismic visualization package on OpenNebula cloud management system

Currently, the exploration of oil and gas have become more complex due to the oil depletion. The increasing difficulties in discovering new hydrocarbon reservoirs using existing technologies have caused an exceptional rise in the cost and risk to discover hydrocarbons. Seismic interpretation is one of the main element in oil exploration. Seismic interpretation software is vital to assist geophysicists to find hydrocarbons trap. However, specialized commercial seismic visualization package is highly priced. Hence, open source seismic visualization package is introduced as an alternative to minimize the cost in oil exploration. The goal of this research is to demonstrate through comparative study of computing functionalities between two different types of open source seismic visualization packages in order to find a preferable one to integrate in cloud infrastructure, OpenNebula cloud. This paper addresses how the author chooses OpendTect over ParaViewGeo as the preferable open source seismic visualization packages by comparing the functionality of the software packages. In addition, a research study on OpenNebula also has been done to understand the working principle of this cloud management system. Furthermore, an experiment has been conducted to test whether or not the preferable open source seismic visualization package is able to be integrated correctly in OpenNebula cloud with high scalability and good performance.